Iron-containing nanominerals for sustainable phosphate management: A comprehensive review and future perspectives

Adsorption, which is a quick and effective method for phosphate management, can effectively address the crisis of phosphorus mineral resources and control eutrophication. Phosphate management systems typically use iron-containing nanominerals (ICNs) with large surface areas and high activity, as well as modified ICNs (mICNs). This paper comprehensively reviews phosphate management by ICNs and mICNs in different water environments. mICNs have a higher affinity for phosphates than ICNs. Phosphate adsorption on ICNs and mICNs occurs through mechanisms such as surface complexation, surface precipitation, electrostatic ligand exchange, and electrostatic attraction. Ionic strength influences phosphate adsorption by changing the surface potential and isoelectric point of ICNs and mICNs. Anions exhibit inhibitory effects on ICNs and mICNs in phosphate adsorption, while cations display a promoting effect. More importantly, high concentrations and molecular weights of natural organic matter can inhibit phosphate adsorption by ICNs and mICNs. Sodium hydroxide has high regeneration capability for ICNs and mICNs. Compared to ICNs with high crystallinity, those with low crystallinity are less likely to desorb. ICNs and mICNs can effectively manage municipal wastewater, eutrophic seawater, and eutrophic lakes. Adsorption of ICNs and mICNs saturated with phosphate can be used as fertilizers in agricultural production. Notably, mICNs and ICNs have positive and negative effects on microorganisms and aquatic organisms in soil. Finally, this study introduces the following: trends and prospects of machine learning-guided mICN design, novel methods for modified ICNs, mICN regeneration, development of mICNs with high adsorption capacity and selectivity for phosphate, investigation of competing ions in different water environments by mICNs, and trends and prospects of in-depth research on the adsorption mechanism of phosphate by weakly crystalline ferrihydrite. This comprehensive review can provide novel insights into the research on high-performance mICNs for phosphate management in the future.

Integrated bioinformatics analysis for exploring potential biomarkers related to Parkinson's disease progression

BACKGROUND

Parkinson's disease (PD) is a progressive neurodegenerative disease with increasing prevalence. Effective diagnostic markers and therapeutic methods are still lacking. Exploring key molecular markers and mechanisms for PD can help with early diagnosis and treatment improvement.

METHODS

Three datasets GSE174052, GSE77668, and GSE168496 were obtained from the GEO database to search differentially expressed circRNA (DECs), miRNAs (DEMis), and mRNAs (DEMs). GO and KEGG enrichment analyses, and protein-protein interaction (PPI) network construction were implemented to explore possible actions of DEMs. Hub genes were selected to establish circRNA-related competing endogenous RNA (ceRNA) networks.

RESULTS

There were 1005 downregulated DECs, 21 upregulated and 21 downregulated DEMis, and 266 upregulated and 234 downregulated DEMs identified. The DEMs were significantly enriched in various PD-associated functions and pathways such as extracellular matrix organization, dopamine synthesis, PI3K-Akt, and calcium signaling pathways. Twenty-one hub genes were screened out, and a PD-related ceRNA regulatory network was constructed containing 31 circRNAs, one miRNA (miR-371a-3p), and one hub gene (KCNJ6).

CONCLUSION

We identified PD-related molecular markers and ceRNA regulatory networks, providing new directions for PD diagnosis and treatment.

Corrigendum to "Anti-tumor effect and mechanism of the total biflavonoid extract from S doederleinii on human cervical cancer cells in vitro and in vivo" [Heliyon 10(2) January 2024 e24778]

[This corrects the article DOI: 10.1016/j.heliyon.2024.e24778.].

Search for exotic decays of the Higgs boson to a pair of pseudoscalars in the μμbb and ττbb final states

A search for exotic decays of the Higgs boson (H ) with a mass of 125Ge V to a pair of light pseudoscalars a 1 is performed in final states where one pseudoscalar decays to two b quarks and the other to a pair of muons or τ leptons. A data sample of proton-proton collisions at s = 13 Te V corresponding to an integrated luminosity of 138fb - 1 recorded with the CMS detector is analyzed. No statistically significant excess is observed over the standard model backgrounds. Upper limits are set at 95% confidence level (CL ) on the Higgs boson branching fraction to μ μ b b and to τ τ b b , via a pair of a 1 s. The limits depend on the pseudoscalar mass m a 1 and are observed to be in the range (0.17-3.3) × 10 - 4 and (1.7-7.7) × 10 - 2 in the μ μ b b and τ τ b b final states, respectively. In the framework of models with two Higgs doublets and a complex scalar singlet (2HDM+S), the results of the two final states are combined to determine upper limits on the branching fraction B ( H → a 1 a 1 → ℓ ℓ b b ) at 95% CL , with ℓ being a muon or a τ lepton. For different types of 2HDM+S, upper bounds on the branching fraction B ( H → a 1 a 1 ) are extracted from the combination of the two channels. In most of the Type II 2HDM+S parameter space, B ( H → a 1 a 1 ) values above 0.23 are excluded at 95% CL for m a 1 values between 15 and 60Ge V .

Anti-artifacts techniques for neural recording front-ends in closed-loop brain-machine interface ICs

In recent years, thanks to the development of integrated circuits, clinical medicine has witnessed significant advancements, enabling more efficient and intelligent treatment approaches. Particularly in the field of neuromedical, the utilization of brain-machine interfaces (BMI) has revolutionized the treatment of neurological diseases such as amyotrophic lateral sclerosis, cerebral palsy, stroke, or spinal cord injury. The BMI acquires neural signals via recording circuits and analyze them to regulate neural stimulator circuits for effective neurological treatment. However, traditional BMI designs, which are often isolated, have given way to closed-loop brain-machine interfaces (CL-BMI) as a contemporary development trend. CL-BMI offers increased integration and accelerated response speed, marking a significant leap forward in neuromedicine. Nonetheless, this advancement comes with its challenges, notably the stimulation artifacts (SA) problem inherent to the structural characteristics of CL-BMI, which poses significant challenges on the neural recording front-ends (NRFE) site. This paper aims to provide a comprehensive overview of technologies addressing artifacts in the NRFE site within CL-BMI. Topics covered will include: (1) understanding and assessing artifacts; (2) exploring the impact of artifacts on traditional neural recording front-ends; (3) reviewing recent technological advancements aimed at addressing artifact-related issues; (4) summarizing and classifying the aforementioned technologies, along with an analysis of future trends.

Excitation functions for fast neutron induced reactions on iron and lead

Cross sections of the 54Fe(n,p)54Mn, 54Fe(n,α)51Cr, 56Fe(n,p)56Mn and 204Pb (n,2n)203Pb reactions induced by D-T neutrons were obtained with activation method and γ-ray spectrometry technique. Experimental values measured in this work are consistent with most of the previous literature data. These reactions cross sections were theoretically calculated by using the TALYS-1.96 and EMPIRE-3.2.3 codes from threshold up to 20 MeV, and significant discrepancies were found between calculated results and experiment data. In addition, experimental values are compared with evaluated nuclear data of the CENDL-3.2, ENDF/B-VIII.0, JENDL-5, BROND-3.1 and JEFF-3.3 libraries, and significant difference was found for the 54Fe(n,α)51Cr reaction in ENDF/B-VIII.0 library but not for other reactions.

Phase Engineering of Zirconium MOFs Enables Efficient Osmotic Energy Conversion: Structural Evolution Unveiled by Direct Imaging

Creating structural defects in a controlled manner within metal-organic frameworks (MOFs) poses a significant challenge for synthesis, and concurrently, identifying the types and distributions of these defects is also a formidable task for characterization. In this study, we demonstrate that by employing 2-sulfonylterephthalic acid as the ligand for synthesizing Zr (or Hf)-based MOFs, a crystal phase transformation from the common fcu topology to the rare jmt topology can be easily facilitated using a straightforward mixed-solvent strategy. The jmt phase, characterized by an extensively open framework, can be considered a derivative of the fcu phase, generated through the introduction of missing-cluster defects. We have explicitly identified both MOF phases, their intermediate states, and the novel core-shell structures they form using ultralow-dose high-resolution transmission electron microscopy. In addition to facilitating phase engineering, the incorporation of sulfonic groups in MOFs imparts ionic selectivity, making them applicable for osmotic energy harvesting through mixed matrix membrane fabrication. The membrane containing the jmt-phase MOF exhibits an exceptionally high peak power density of 10.08 W m-2 under a 50-fold salinity gradient (NaCl: 0.5 M|0.01 M), which surpasses the threshold of 5 W m-2 for commercial applications and can be attributed to the combination of large pore size, extensive porosity, and abundant sulfonic groups in this novel MOF material.

Identification of Meloidogyne Species on Traditional Chinese Medicine Plants in the Qinling Mountain Area of China and Their Aggressiveness to Different Medicinal Herbs

Root-knot nematodes (Meloidogyne spp.) are plant-parasitic nematodes that cause serious damage worldwide. There are many species of traditional Chinese medicine (TCM) plants, but only a few have been reported to be infected by Meloidogyne species. From 2020 to 2022, a survey was conducted in the Qinling mountain area, which is the main production region of TCM plants in China. Obvious galling symptoms were observed on the root systems of 15 species of TCM plants. Females were collected from diverse diseased TCM plants and subsequently identified at morphological and molecular levels. Among the 20 diseased root samples collected, Meloidogyne hapla populations were identified in 12 samples (60%), and M. incognita populations were identified in eight samples (40%). Among the 15 species of diseased TCM plants, eight species, namely, Scutellaria baicalensis, Leonurus japonicus, Dioscorea zingiberensis, Cornus officinalis, Viola philippica, Achyranthes bidentata, Senecio scandens, and Plantago depressa, were reported to be infected by Meloidogyne species for the first time. The host status of five species of TCM plants for two M. hapla isolates and one M. incognita isolate from TCM plants in this study was then evaluated. Differences in TCM plants' response to nematode infection were apparent when susceptibility was evaluated by the egg counts per gram of fresh root and the reproduction factor of the nematodes. Among the five species of TCM plants tested, Salvia miltiorrhiza and Gynostemma pentaphyllum were the most susceptible, while S. baicalensis and V. philippica were not considered suitable hosts for M. hapla or M. incognita.

A Spiking Artificial Vision Architecture Based on Fully Emulating the Human Vision

Intelligent vision necessitates the deployment of detectors that are always-on and low-power, mirroring the continuous and uninterrupted responsiveness characteristic of human vision. Nonetheless, contemporary artificial vision systems attain this goal by the continuous processing of massive image frames and executing intricate algorithms, thereby expending substantial computational power and energy. In contrast, biological data processing, based on event-triggered spiking, has higher efficiency and lower energy consumption. Here, this work proposes an artificial vision architecture consisting of spiking photodetectors and artificial synapses, closely mirroring the intricacies of the human visual system. Distinct from previously reported techniques, the photodetector is self-powered and event-triggered, outputting light-modulated spiking signals directly, thereby fulfilling the imperative for always-on with low-power consumption. With the spiking signals processing through the integrated synapse units, recognition of graphics, gestures, and human action has been implemented, illustrating the potent image processing capabilities inherent within this architecture. The results prove the 90% accuracy rate in human action recognition within a mere five epochs utilizing a rudimentary artificial neural network. This novel architecture, grounded in spiking photodetectors, offers a viable alternative to the extant models of always-on low-power artificial vision system.

CD-Net: Cascaded 3D Dilated convolutional neural network for pneumonia lesion segmentation

COVID-19 is a global pandemic that has caused significant global, social, and economic disruption. To effectively assist in screening and monitoring diagnosed cases, it is crucial to accurately segment lesions from Computer Tomography (CT) scans. Due to the lack of labeled data and the presence of redundant parameters in 3D CT, there are still significant challenges in diagnosing COVID-19 in related fields. To address the problem, we have developed a new model called the Cascaded 3D Dilated convolutional neural network (CD-Net) for directly processing CT volume data. To reduce memory consumption when cutting volume data into small patches, we initially design a cascade architecture in CD-Net to preserve global information. Then, we construct a Multi-scale Parallel Dilated Convolution (MPDC) block to aggregate features of different sizes and simultaneously reduce the parameters. Moreover, to alleviate the shortage of labeled data, we employ classical transfer learning, which requires only a small amount of data while achieving better performance. Experimental results conducted on the different public-available datasets verify that the proposed CD-Net has reduced the negative-positive ratio and outperformed other existing segmentation methods while requiring less data.

Observation of Seven Astrophysical Tau Neutrino Candidates with IceCube

We report on a measurement of astrophysical tau neutrinos with 9.7 yr of IceCube data. Using convolutional neural networks trained on images derived from simulated events, seven candidate ν_{τ} events were found with visible energies ranging from roughly 20 TeV to 1 PeV and a median expected parent ν_{τ} energy of about 200 TeV. Considering backgrounds from astrophysical and atmospheric neutrinos, and muons from π^{±}/K^{±} decays in atmospheric air showers, we obtain a total estimated background of about 0.5 events, dominated by non-ν_{τ} astrophysical neutrinos. Thus, we rule out the absence of astrophysical ν_{τ} at the 5σ level. The measured astrophysical ν_{τ} flux is consistent with expectations based on previously published IceCube astrophysical neutrino flux measurements and neutrino oscillations.

[Effect of SHP-1 knockout in airway epithelial cells on emphysema phenotype in chronic obstructive pulmonary disease in mice]

Objective: To construct and characterize conditional Src homology region 2 protein tyrosine phosphatase 1 (SHP-1) knockout mice in airway epithelial cells and to observe the effect of defective SHP-1 expression in airway epithelial cells on the emphysema phenotype in chronic obstructive pulmonary disease (COPD). Methods: To detect the expression of SHP-1 in the airway epithelium of COPD patients. CRISPR/Cas9 technology was used to construct SHP-1flox/flox transgenic mice, which were mated with airway epithelial Clara protein 10-cyclase recombinase and estrogen receptor fusion transgenic mice (CC10-CreER+/+), and after intraperitoneal injection of tamoxifen, airway epithelial SHP-1 knockout mice were obtained (SHP-1flox/floxCC10-CreER+/-, SHP-1Δ/Δ). Mouse tail and lung tissue DNA was extracted and PCR amplified to discriminate the genotype of the mice; the knockout effect of SHP-1 gene in airway epithelial cells was verified by qRT-PCR, Western blotting, and immunofluorescence. In addition, an emphysema mouse model was constructed using elastase to assess the severity of emphysema in each group of mice. Results: Airway epithelial SHP-1 was significantly downregulated in COPD patients. Genotyping confirmed that SHP-1Δ/Δ mice expressed CC10-CreER and SHP-1-flox. After tamoxifen induction, we demonstrated the absence of SHP-1 protein expression in airway epithelial cells of SHP-1Δ/Δ mice at the DNA, RNA, and protein levels, indicating that airway epithelial cell-specific SHP-1 knockout mice had been successfully constructed. In the emphysema animal model, SHP-1Δ/Δ mice had a more severe emphysema phenotype compared with the control group, which was manifested by disorganization of alveolar structure in lung tissue and rupture and fusion of alveolar walls to form pulmonary alveoli. Conclusions: The present study successfully established and characterized the SHP-1 knockout mouse model of airway epithelial cells, which provides a new experimental tool for the in-depth elucidation of the role of SHP-1 in the emphysema process of COPD and its mechanism.

Dynamics of magnetization at infinite temperature in a Heisenberg spin chain

Understanding universal aspects of quantum dynamics is an unresolved problem in statistical mechanics. In particular, the spin dynamics of the one-dimensional Heisenberg model were conjectured as to belong to the Kardar-Parisi-Zhang (KPZ) universality class based on the scaling of the infinite-temperature spin-spin correlation function. In a chain of 46 superconducting qubits, we studied the probability distribution of the magnetization transferred across the chain's center, [Formula: see text]. The first two moments of [Formula: see text] show superdiffusive behavior, a hallmark of KPZ universality. However, the third and fourth moments ruled out the KPZ conjecture and allow for evaluating other theories. Our results highlight the importance of studying higher moments in determining dynamic universality classes and provide insights into universal behavior in quantum systems.

Intelligently Quantifying the Entire Irregular Dental Structure

Quantitative analysis of irregular anatomical structures is crucial in oral medicine, but clinicians often typically measure only several representative indicators within the structure as references. Deep learning semantic segmentation offers the potential for entire quantitative analysis. However, challenges persist, including segmentation difficulties due to unclear boundaries and acquiring measurement landmarks for clinical needs in entire quantitative analysis. Taking the palatal alveolar bone as an example, we proposed an artificial intelligence measurement tool for the entire quantitative analysis of irregular dental structures. To expand the applicability, we have included lightweight networks with fewer parameters and lower computational demands. Our approach finally used the lightweight model LU-Net, addressing segmentation challenges caused by unclear boundaries through a compensation module. Additional enamel segmentation was conducted to establish a measurement coordinate system. Ultimately, we presented the entire quantitative information within the structure in a manner that meets clinical needs. The tool achieved excellent segmentation results, manifested by high Dice coefficients (0.934 and 0.949), intersection over union (0.888 and 0.907), and area under the curve (0.943 and 0.949) for palatal alveolar bone and enamel in the test set. In subsequent measurements, the tool visualizes the quantitative information within the target structure by scatter plots. When comparing the measurements against representative indicators, the tool's measurement results show no statistically significant difference from the ground truth, with small mean absolute error, root mean squared error, and errors interval. Bland-Altman plots and intraclass correlation coefficients indicate the satisfactory agreement compared with manual measurements. We proposed a novel intelligent approach to address the entire quantitative analysis of irregular image structures in the clinical setting. This contributes to enabling clinicians to swiftly and comprehensively grasp structural features, facilitating the design of more personalized treatment plans for different patients, enhancing clinical efficiency and treatment success rates in turn.

Stable quantum-correlated many-body states through engineered dissipation

Engineered dissipative reservoirs have the potential to steer many-body quantum systems toward correlated steady states useful for quantum simulation of high-temperature superconductivity or quantum magnetism. Using up to 49 superconducting qubits, we prepared low-energy states of the transverse-field Ising model through coupling to dissipative auxiliary qubits. In one dimension, we observed long-range quantum correlations and a ground-state fidelity of 0.86 for 18 qubits at the critical point. In two dimensions, we found mutual information that extends beyond nearest neighbors. Lastly, by coupling the system to auxiliaries emulating reservoirs with different chemical potentials, we explored transport in the quantum Heisenberg model. Our results establish engineered dissipation as a scalable alternative to unitary evolution for preparing entangled many-body states on noisy quantum processors.

Observation of WWγ Production and Search for Hγ Production in Proton-Proton Collisions at sqrt[s]=13 TeV

The observation of WWγ production in proton-proton collisions at a center-of-mass energy of 13 TeV with an integrated luminosity of 138  fb^{-1} is presented. The observed (expected) significance is 5.6 (5.1) standard deviations. Events are selected by requiring exactly two leptons (one electron and one muon) of opposite charge, moderate missing transverse momentum, and a photon. The measured fiducial cross section for WWγ is 5.9±0.8(stat)±0.8(syst)±0.7(modeling)  fb, in agreement with the next-to-leading order quantum chromodynamics prediction. The analysis is extended with a search for the associated production of the Higgs boson and a photon, which is generated by a coupling of the Higgs boson to light quarks. The result is used to constrain the Higgs boson couplings to light quarks.

New Structures in the J/ψJ/ψ Mass Spectrum in Proton-Proton Collisions at sqrt[s]=13 TeV

A search is reported for near-threshold structures in the J/ψJ/ψ invariant mass spectrum produced in proton-proton collisions at sqrt[s]=13  TeV from data collected by the CMS experiment, corresponding to an integrated luminosity of 135  fb^{-1}. Three structures are found, and a model with quantum interference among these structures provides a good description of the data. A new structure is observed with a local significance above 5 standard deviations at a mass of 6638_{-38}^{+43}(stat)_{-31}^{+16}(syst)  MeV. Another structure with even higher significance is found at a mass of 6847_{-28}^{+44}(stat)_{-20}^{+48}(syst)  MeV, which is consistent with the X(6900) resonance reported by the LHCb experiment and confirmed by the ATLAS experiment. Evidence for another new structure, with a local significance of 4.7 standard deviations, is found at a mass of 7134_{-25}^{+48}(stat)_{-15}^{+41}(syst)  MeV. Results are also reported for a model without interference, which does not fit the data as well and shows mass shifts up to 150 MeV relative to the model with interference.

Resveratrol Attenuates Rheumatoid Arthritis Induce Neutrophil Extracellular Traps via TLR-4 Mediated Inflammation in C57BL/6 Mice

The objective of this study was to evaluate whether RSV inhibits neutrophil extracellular traps (NETs) that induce joint hyperalgesia in C57BL/6 mice after adjuvant-induced arthritis. A subplantar injection of Freund's complete adjuvant was administered to C57BL/6 mice on day 0 for immunization in the AIA model. Resveratrol (RSV, 25 mg/kg) was administered intraperitoneally once daily starting on day 22 and continuing for two weeks. The effects of mechanical hyperalgesia and edema formation have been assessed in addition to histopathological scoring. Mice were sacrificed on day 35 to determine cytokine levels and PADI4 and COX-2 expression levels. ELISA was used to quantify neutrophil extracellular traps (NETs) along with neutrophil elastase-DNA and myeloperoxidase-DNA complexes in neutrophils. An immunohistochemical stain was performed on knee joints to determine the presence of nuclear factor kappa B p65 (NF-kappaB p65). AIA mice were found to have higher levels of NET in joints and their joint cells demonstrated an increased expression of the PADI4 gene. Treatment with RSV in AIA mice (25 mg/kg, i.p.) significantly (P<0.05) inhibited joint hyperalgesia, resulting in a significant increase in mechanical threshold, a decrease in articular edema, a decrease in the production of inflammatory cytokines, increased COX-2 expression, and a decrease in the immunostaining of NF-kappaB. Furthermore, treatment with RSV significantly reduced the amount of neutrophil elastase (NE)-DNA and MPO-DNA complexes, which were used as indicators of NET formation (P<0.05). This study indicates that RSV reduces NET production and hyperalgesia by reducing inflammation mediated by PADI4 and COX-2. According to these data, NETs contribute to joint pain and resveratrol can be used to treat pain in RA through this pathway.

Bioinformatics Analysis and Experimental Validation for Exploring Key Molecular Markers for Glioblastoma

Glioblastoma (GBM) is the most common primary intracranial malignancy with a very low survival rate. Exploring key molecular markers for GBM can help with early diagnosis, prognostic prediction, and recurrence monitoring. This study aims to explore novel biomarkers for GBM via bioinformatics analysis and experimental verification. Dataset GSE103229 was obtained from the GEO database to search differentially expressed lncRNA (DELs), mRNAs (DEMs), and miRNAs (DEMis). Hub genes were selected to establish competing endogenous RNA (ceRNA) networks. The GEPIA database was employed for the survival analysis and expression detection of hub genes. Hub gene expression in GBM tissue samples and cell lines was validated using RT-qPCR. Western blotting was employed for protein expression evaluation. SYT1 overexpression vector was transfected in GBM cells. CCK-8 assay and flow cytometry were performed to detect the malignant phenotypes of GBM cells. There were 901 upregulated and 1086 downregulated DEMs identified, which were prominently enriched in various malignancy-related functions and pathways. Twenty-two hub genes were selected from PPI networks. Survival analysis and experimental validation revealed that four hub genes were tightly associated with GBM prognosis and progression, including SYT1, GRIN2A, KCNA1, and SYNPR. The four genes were significantly downregulated in GBM tissues and cell lines. Overexpressing SYT1 alleviated the proliferation and promoted the apoptosis of GBM cells in vitro. We identify four genes that may be potential molecular markers of GBM, which may provide new ideas for improving early diagnosis and prediction of the disease.

Low rCBV values in glioblastoma tumor progression under chemoradiotherapy

PURPOSE

After standard treatment for glioblastoma, perfusion MRI remains challenging for differentiating tumor progression from post-treatment changes. Our objectives were (1) to correlate rCBV values at diagnosis and at first tumor progression and (2) to analyze the relationship of rCBV values at tumor recurrence with enhancing volume, localization of tumor progression, and time elapsed since the end of radiotherapy in tumor recurrence.

METHODS

Inclusion criteria were (1) age > 18 years, (2) histologically confirmed glioblastoma treated with STUPP regimen, and (3) tumor progression according to RANO criteria > 12 weeks after radiotherapy. Co-registration of segmented enhancing tumor VOIs with dynamic susceptibility contrast perfusion MRI was performed using Olea Sphere software. For tumor recurrence, we correlated rCBV values with enhancing tumor volume, with recurrence localization, and with time elapsed from the end of radiotherapy to progression. Analyses were performed with SPSS software.

RESULTS

Sixty-four patients with glioblastoma were included in the study. Changes in rCBV values between diagnosis and first tumor progression were significant (p < 0.001), with a mean and median decreases of 32% and 46%, respectively. Mean rCBV values were also different (p < 0.01) when tumors progressed distally (radiation field rCBV values of 1.679 versus 3.409 distally). However, changes and, therefore, low rCBV values after radiotherapy in tumor recurrence were independent of time.

CONCLUSION

Chemoradiation alters tumor perfusion and rCBV values may be decreased in the setting of tumor progression. Changes in rCBV values with respect to diagnosis, with low rCBV in tumor progression, are independent of time but related to the site of recurrence.

[Advances in the technology of surgical treatment for atlantoaxial dislocation]

The etiology and pathological morphology of atlantoaxial dislocation (AAD) are complex. Based on the pathological anatomical characteristics of AAD, combined with clinical techniques, it is essential to formulate reasonable classification criteria and develop corresponding treatment strategies for different types of AAD. The satisfactory outcome of surgical treatment for AAD can only be achieved through the comprehensive application of various atlantoaxial reduction techniques, tension band releasing techniques, internal fixation and fusion techniques. This article discusses the latest advancements in surgical treatment techniques for AAD, thoroughly explores treatment strategies based on different types of AAD, and analyzes the practicality and effectiveness of clinical classification and treatment strategies. The posterior atlantoaxial facet releasing and distraction compression reduction technique may pose challenges to traditional treatment strategies in the future. In the development of surgical treatment techniques for AAD, microspinal surgical techniques may play a significant role in improving surgical methods and enhancing treatment outcomes.

[Clinical evaluation methods for craniovertebral junction abnormalities]

Craniovertebral junction malformation is a congenital malformation located in the foramen magnum and upper cervical spine, including bone and nerve malformation, resulting in motor and sensory disorders, cerebellar and lower cranial nerves, etc. The evaluation methods of clinical symptoms and efficacy of craniovertebral junction malformation are important for the surgical indications and effects, mainly including the evaluation of clinical symptoms and the quality of life. At present, the commonly used methods in clinical work and literature are the Japanese orthopaedic association scores, visual analogue scales, 36-item short-form health survey, etc. Most of these clinical evaluations are not aimed at craniovertebral junction diseases but focus on the description of a certain type of clinical symptoms. Chicago Chiari outcome scale and syringomyelia outcome scale of Xuanwu hospital are dedicated to Craniovertebral junction malformation, but more clinical studies are needed to prove their effectiveness. Based on the literature reports, this article reviewed the previous clinical evaluation methods of craniovertebral junction malformation and discusses their applications and limitations.

A two-dimensional metal-organic framework assembled from scandium-based cages for the selective capture of sulfur hexafluoride

Herein, we report the synthesis of a two-dimensional metal-organic framework (MOF), assembled from octahedral metal-organic cages featuring phenanthroline-based carboxylate linkers and μ3-oxo-centered trinuclear Sc(III) inorganic building blocks. We study the performance of this MOF towards the capture of sulfur hexafluoride (SF6). On account of its structural features and porous nature, this MOF displays an SF6 uptake capacity of 0.92 mmol g-1 at 0.1 bar and an isosteric heat of adsorption of about 30.7 kJ mol-1 for SF6, illustrating its potential application for the selective capture of SF6 from N2. In addition, we study the adsorptive binding mechanism of SF6 and N2 inside this MOF via molecular simulations.

Removing polyfluoroalkyl substances (PFAS) from wastewater with mixed matrix membranes

Polyfluoroalkyl and perfluoroalkyl (PFAS) chemicals are fluorinated and exhibit complicated behavior. They are determined and highly resistant to ecological modifications that render plants ecologically robust. Thermal stability and water and oil resistance are examples of material qualities. Their adverse consequences are causing increasing worry due to their bioaccumulative nature in humans and other creatures. Direct data indicates that PFAS exposure in humans causes endocrine system disruption, immune system suppression, obesity, increased cholesterol, and cancer. Several PFASs are present in drinking water at low doses and may harm people. These cancer-causing PFAS have caused concern for water bodies all around the globe. Analytical techniques are used to identify and measure PFAS in an aqueous medium (membrane). Furthermore, a deeper explanation is provided for PFAS removal methods, including mixed matrix membrane (MMM) technology. By removing over 99 % of the PFAS from wastewater, MMMs may effectively remove PFAS from sewage when the support matrix contains adsorbing components. Furthermore, we consider several factors affecting the removal of PFAS and practical sorption methods for PFAS onto various adsorbents.